Instructions to use vonewman/mind_audio_classification_model with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use vonewman/mind_audio_classification_model with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("audio-classification", model="vonewman/mind_audio_classification_model")# Load model directly from transformers import AutoProcessor, AutoModelForAudioClassification processor = AutoProcessor.from_pretrained("vonewman/mind_audio_classification_model") model = AutoModelForAudioClassification.from_pretrained("vonewman/mind_audio_classification_model", device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Xet hash:
- 3921e50c2caf8afb5e98d8b28d1c38bc5ea400c379b4bcffe39dfc0b48db32c6
- Size of remote file:
- 4.09 kB
- SHA256:
- 779fa00a70d976f3684bdcb185c3c81349754d06978ade673030e9d0c2372691
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